A regression model to predict Y , the state burglary rate per 100,000 people for

Question

A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies, X3 = 2004 federal expenditures per capita (a leading predictor), and X4 = 2005 high school graduation percentage.

Fill in the values in the table given here for a two-tailed test at = 0.01 with 33 d.f. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p-values to 4 decimal places.)

  

A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies, X3 = 2004 federal expenditures per capita (a leading predictor), and X4 = 2005 high school graduation percentage.

Explanation / Answer

t calc =coefficient/SE ; and p value can be taken by considering degree of freedom =33

  Predictor Coefficient SE      tcalc      p-value   Intercept 4,579.5465 791.5050 5.786 0.0000   AgeMed -27.2920 12.1893 -2.239 0.0320   Bankrupt 19.5612 12.0754 1.620 0.1148   FedSpend -0.0132 0.0116 -1.138 0.2633   HSGrad% -27.5839 7.1731 -3.845 0.0005

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